Let’s make this a weekly builder thread.

Whether you’re working on AI apps, agents, LLM tools, ML projects, robotics, research, startups, or automations — drop what you’re building below.

3 simple questions:

1. What are you building?
Share your project, idea, prototype, or experiment.

2. What are you learning?
Could be a model, framework, paper, tool, or skill.

3. What’s blocking you right now?
Maybe someone here can help.

The goal is to make r/SinceAI a place where builders can share progress, get feedback, meet serious people, and learn faster together.

If you’re lurking, this is a great first thread to comment on.

A new study analyzed 25 million comments from Reddit and Hacker News.

The strange result wasn’t that people are good at detecting AI.

It was the opposite.

The writing patterns that actually distinguish AI text from human text did not predict which human-written comments people accused of being AI.

We’re not detecting bots. We’re punishing a vibe.

Write clearly? Bot.
Use an em dash? ChatGPT.
Structure an argument? AI slop.
Write badly on purpose? Finally, a real human.

The Turing test used to ask whether a machine could convince us it was human.

Now humans have to convince the internet they aren’t machines.

So let’s test Reddit.

Post a 2–3 sentence opinion about AI below. It can be written entirely by you or entirely by an AI. Don’t reveal which.

Everyone else replies:

HUMAN or AI — and why.

After at least three guesses, reveal the answer.

No AI detectors. No checking profiles. Judge only the text.

I think this thread will prove that most of us have absolutely no idea.

most people spend far too long watching courses, reading tutorials and collecting certificates.

After you understand the basics, the fastest way to improve is to work on a real problem where:
-the data is messy
-the requirements are unclear
-your first model fails
-someone actually expects the solution to work

One serious project can teach you more than months of passive studying.

Or what you think?

Models are becoming better, cheaper, and increasingly interchangeable.

But most AI systems still cannot actually do anything.

They can recommend a purchase, but not place the order.
Detect a production problem, but not stop the machine.
Suggest a treatment, but not access the patient workflow.
Find financial risk, but not move the money.

The scarce asset may not be intelligence anymore.

It may be permission:

• access to proprietary data
• authority to change real systems
• trust inside regulated industries
• distribution to actual users

A chatbot can suggest. A company with permission can act.

If intelligence becomes a commodity, who owns the permission layer in your industry?

Let’s make this a weekly builder thread.

Whether you’re working on AI apps, agents, LLM tools, ML projects, robotics, research, startups, or automations — drop what you’re building below.

3 simple questions:

1. What are you building?
Share your project, idea, prototype, or experiment.

2. What are you learning?
Could be a model, framework, paper, tool, or skill.

3. What’s blocking you right now?
Maybe someone here can help.

The goal is to make r/SinceAI a place where builders can share progress, get feedback, meet serious people, and learn faster together.

If you’re lurking, this is a great first thread to comment on.

Someone just used Claude Fable 5 to build a 45,000-line Minecraft-like game in roughly a week.

Not one prompt but almost, still a pretty clear signal.

If custom software becomes dramatically cheaper to build, where does durable value move?

Hardware + software? Proprietary data? Distribution? Or industries like construction, energy and manufacturing where software has to meet the physical world?

Where would you build today?

Let’s make this a weekly builder thread.

Whether you’re working on AI apps, agents, LLM tools, ML projects, robotics, research, startups, or automations — drop what you’re building below.

3 simple questions:

1. What are you building?
Share your project, idea, prototype, or experiment.

2. What are you learning?
Could be a model, framework, paper, tool, or skill.

3. What’s blocking you right now?
Maybe someone here can help.

The goal is to make r/SinceAI a place where builders can share progress, get feedback, meet serious people, and learn faster together.

If you’re lurking, this is a great first thread to comment on.

Let’s make this a weekly builder thread.

Whether you’re working on AI apps, agents, LLM tools, ML projects, robotics, research, startups, or automations — drop what you’re building below.

3 simple questions:

1. What are you building?
Share your project, idea, prototype, or experiment.

2. What are you learning?
Could be a model, framework, paper, tool, or skill.

3. What’s blocking you right now?
Maybe someone here can help.

The goal is to make r/SinceAI a place where builders can share progress, get feedback, meet serious people, and learn faster together.

If you’re lurking, this is a great first thread to comment on.

I’ve been switching back and forth between Opus and GPT-5.5 lately, mostly for coding, debugging and product/spec writing.

My rough feeling so far:

GPT-5.5 feels better as a daily “get things done” model. It’s fast enough, usually smart enough, and feels more cost-effective for normal builder work.

Opus still feels stronger when I’m stuck on something messy, like architecture decisions, weird bugs, or when I want a second opinion that thinks a bit differently.

A few people around me have also started using GPT-5.5 more often, but I’m not sure if that’s just hype / novelty bias.

Curious what people here are actually using:

• What’s your default model right now?
• Is Opus still worth the extra cost for you?
• For coding specifically, which model helps you ship faster?
• Do you use one model for daily work and another for harder reasoning?

[ Removed by Reddit on account of violating the content policy. ]